Pixel-level high-throughput estimation of crop photosynthetic phenotyping parameters using a multi-task deep learning framework
提出像素级多任务深度学习框架，从高光谱数据高通量估算作物光合表型参数。
农业AI与大模型
人工智能算法、大模型与决策支持系统
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MSO-Det: A multi-level synergistic optimization framework for robust spike object detection in field scenes
提出MSO-Det多级协同优化框架，用于田间场景下鲁棒的穗部目标检测。
Explainable growth stage classification of cacao (Theobroma cacao L.) leaves and key feature visualization using vision transformer and transfer learning
用ViT和迁移学习对可可叶D、E期进行可解释分类，准确率达97%。
Spatiotemporal Deep Learning for Rice Plant Height Estimation from Multi-Temporal UAV RGB Imagery
提出Rice-STNet时空深度学习框架，用多时相无人机RGB影像估算水稻株高。
Automated detection of visible venation patterns in cowpea leaves under agricultural engineering
用RGB卷积神经网络自动分类豇豆叶片可见脉纹，区分健康与结构胁迫样本。
PlantC2USeg: Cross-Scale Consistent Pre-Training for Few-Shot Unified Plant Point Cloud Segmentation
提出PlantC2USeg，通过跨尺度一致性预训练实现少样本植物点云分割。
RGB-based phenotyping of grapevine leaves reveals stronger cultivar discrimination on the abaxial surface
比较葡萄叶片上下表面颜色特征，发现下表面更能区分品种。